Sunday, May 11, 2014

Recently there has been more said on USHCN adjustments. My recent post on a Steven Goddard plot posted at WUWT produced a response, which conceded the plot was wrong, but Anthony said, defensively," The one thing common to all of it though is that it cools the past, and many people don’t see that as a justifiable or even an honest adjustment."

I've previously written in defence of TOBS, as an adjustment which is not only justifiable but necessary. The information requiring it is staring analysts in the face, and they would be negligent to ignore it. I showed a hourly analysis at Ft Collins, Colo, of the effect of the TOBS bias.

But recently, Steven Mosher reminded that the much-loved (by sceptics) John Daly site had posted a much more comprehensive survey, by Jerry Brennan in November 2005. The analysis is here, and his summary datafile, which I will use, is here (text, 29kb), which also identifies the stations.

There are other extensive results files there too, but unfortunately, it's all a jumble of numbers. AFAIK, no graphics. So I thought I would provide some. Below is a histogram of the effect of changing TOB from 5pm to 9am for each of the 190 stations considered by Jerry, and of subsequent changes to midnight (standard). There is also a table from the original paper by Karl et el, 1986, which showed that over the years in the US, about 30% of stations made such a change to 1986. Many more stations would have changed to effectively midnight reporting when MMTS came in. Ther mean effect of the change is 0.66°C cooling. It is no surprise that USHCN adjustments have the effect of "cooling the past".
In the original Karl et el, 1986 paper, there is the following table showing what changes had been made to observing times:

Because evening TOB has a warm bias, through double counting very warm afternoons, the change to 9am has a cooling effect. Here is a histogram of the putative effects for the 190 stations of changing from 5pm observing time to 9am. Positive effect indicates (in °C) the bias that has to be subtracted from temperatures before the change.

The standard setting is midnight, which some stations already observed, and which would become the setting after MMTS conversion. So here is the required adjustment (in °C) for changing from 5pm to midnight:

In fact, midnight mostly has a slightly greater cool bias than 9am. This can be seen in the plot of change to midnight from 9am:

These are large changes, which don't of course apply in full to all stations. A small number were already using midnight. The rest will mostly need some kind of TOBS adjustment, which will "cool the past". But on the evidence, there's no choice.

25 comments:

Congratulations on the increasing influence of your blog. Was Watt's appearance a first for you? I had a look at his post, written in collaboration with Zeke, which clearly demonstrates your influence there. Amusing to see that Anthony' s acolytes seem now to be in rebellion against him in his criticisms of their new champion, Steven Goddard. That said the WUWT crowd has clearly degenerated. While the contributions in the past were pretty flaky they did at least have a semblance of sound science (e.g. Eschenbach, Orssengo). One wonders whither they have decamped.

One of the aforementioned acolytes pronounced that only those weather stations that do not require any adjustment should be used for constructing temperature series. It would be interesting to know how many stations would fall into that category even back to, say, 1945.

Nick,Thank you for your frequent and always useful comments on other blogs which i think bring clarity to some otherwise murky thinking; and of course your work here, as well.

I do have a question which I've been mulling over.

I suspect that a TOB change in raw data will almost always show as a step change. A station move might also produce a detectable step change. Is it also possible to detect step changes in the data which might have persistence equivalent to a TOB change without knowing where to look? Might one infer anything useful from a detected step change lacking a note in the metadata?I suppose I'm suggesting data mining, but in some of my previous activities, data mining did produce useful insights. Would it here, do you think?

Thanks, JFYes, if TOBS changes weren't allowed for by metadata, they should appear as a step change in the data. TOBS is the first step in NCDC processing, so that step shouldn't appear in later processing.

The homogenisation algorithms are a sort of data mining, and should pick it up (if not previously removed). But TOBS changes are near the bottom of the range they would detect. The reason they are important is that they tend to all go one way, since they reflect responses to NWS policies that affected all COOPs. So it is fortunate that metadata can catch them.

I think the thing I was getting at is other unidentified step changes. You would have to look for them in the unprocessed data. Are there unidentified step changes in there? I would think there must be.

I'm sure there are lots of unidentified step changes. That's what the homogenisation focusses on. I think you'd probably want to check diractly against the metadata. That's a big job - I haven't done it. A change of a few tenths is hard to spot.

Nick,Thanks much for helping me with this. I suspected it was the case and wouldn't at all be surprised that there are papers out there which deal with this. I need to look into this some more to satisfy my own curiosity.

Good post Nick. Trying to explain MMTS and TOBs over in the WUWT comment thread seems somewhat sisyphean at times, but at least some folks now realize that averaging absolute temperatures is a bad idea :-p

Didn't notice that comment by Anthony (which, I think, was quoted as an email from him in the post over at WUWT). I for one don't think that homogenization is unjustified, and think the PHA does a pretty good job (having done some work myself testing it).

On the quote, yes, it's in an email and worded to avoid saying that you both agree, as I'm sure you don't. But when challenged as to how he could be involved in defending adjustments, that's what he quoted.

It is very up hill and I for one still cannot see "warm bias" when recording Max Min temps.We discussed this on WUWT and you provided an example which in no way explained how the TOR provided a continuous bias to max Min temps and hence the so called Average temp.Can you for instance supply the actual daily values for a couple of those 5pm stations that you quote for say a week or month?Or at least point me to where I can look at them so that I can go through the readings as if I was calculating the Temperatures?

AC,In this post I just plotted the summary data from the John Daly site - links above. There is lots more data there. For my earlier post, I described in more detail a site at Boulder Colorado. This had good hourly data (few gaps). I have put a zipfile of that data and my R code for that post here.

There appears to be something not quite right with the data file you posted, as it does not look anything like your first diurnal pattern graph from your earlier post, there appears to be a 9 hour shift. Does that mean that 0 is not midnight?

I think the data is in GMT, and is converted in the code to Mountain standard time -7,00, which is used in the graphs.

The code is not a good place to srtart if you are learning R. The data file itself is straightforward; just a listing of temperatures and times. The first part of the code is devoted to extracting that. I've put that in a if(T){} block; you should change that to if(F){}, as it is already done. But I'd suggest using whatever you find familiar.

Thanks for the interesting TOBS posts. I've been meaning to try and break down the TOBS adjustment using hourly data, to see how often it gets the adjustment right or wrong. Do you know of any paper that does this? (I'm on pain killers atm, so I apologize if I missed it in your discussions).

Basically what I'm think of looking at are long term station data that have hourly reporting (or better), then "synthesizing" TOBS daily tmin/tmax breaks, and seeing how well the NCDC algorithms work in correcting that. Does this make sense?

Also, regarding homogenization Brandon and I had a bit of discussion relating to the spatial smearing associated with different homogenization methods, specifically BEST. Wonder what your thoughts are on this to?

Both my earlier study (Boulder) and Jerry's looked at hourly data and analysed as if a min/max thermometer was used. So I think do NOAA. Vose et al 2003 describe how they take 500 reference stations with hourly readings (map on Fig 2) and work out the bias for various reading hours. Then to apply TOBS to a given station, they apply the known TOBS history to that data of the nearest of the 500, presumably extraploated periodically.

Thanks for the sympathies, but I was trying to excuse an even greater than normal level of scatterbrained-ness. ;-) Actually I just had some teeth removed (part of my version of "old-timers disease") so the prescribed narcotic painkillers were related to that.

You are correct that it's difficult to find long continuous records, but I suppose as long as we don't have a correlation between weather-related events and signal drop-outs, that this won't matter too much.

I'll give Voss et al a look. The best way to understand these things are to implement them yourself. Thanks for the tips.

Goddard's mistake was to work on absolute temperatures rather than on anomalies.

Accepting that shifting the time of reading (24 hour) from am or pm to midnight can affect the readings, it should not significantly change the anomalies when averaged over a period of one month or more.

Unless, of course, the anomalies are themselves time-biased. By which I mean that the mean anomalies, when temperatures are read at, say, 12.00 pm, 9.00 am and 5.00 pm, all differ by a significant amount. Which, if they do, would rather upset the reason for using anomalies in the first place.